Prediction of Vibration Characteristics of a Composite Rotor Blade via Deep Neural Networks

JOURNAL OF THE KOREAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES(2022)

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Abstract
In this paper, a deep neural network(DNN) model for predicting the vibration characteristics of the composite rotor blade with c-spar cross section was developed. Herein, the present DNN model is defined by using the natural frequencies obtained through the in-house code based on the nonlinear co-rotational(CR) shell element. For the present DNN model, the accuracy of the model was evaluated via the data with a random distribution of thickness and a tendency to decrease in thickness along the blade span.
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Key words
Cross Section Design, Composite Rotor Blade, Natural Frequency, Deep Neural Network
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